A search-engine database is a type of nonrelational database that is dedicated to the search of data content. Search-engine databases use indexes to categorize the similar characteristics among data and facilitate search capability.
- Elasticsearch - A distributed, RESTful search and analytics engine capable of addressing a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data for lightning fast search, fine‑tuned relevancy, and powerful analytics that scale with ease.
- Splunk - A database system designed for extracting structure and analyzing machine-generated data. It takes in data from other databases, web servers, networks, sensors, etc. and then offers services to analyze the data, and produce dashboards, graphs, reports, alerts, and other visualizations.
- Solr - Highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world’s largest internet sites.
- MarkLogic - Includes rich full-text search features, designed to scale to extremely large databases (100s of terabytes or more), all search functionality operates directly against the database, no matter what the database size.
- Algolia - Search as a service and full suite of APIs allow teams to easily develop tailored, fast Search and Discovery experiences that delight and convert.
Search-engine databases are optimized for dealing with data that may be long, semistructured, or unstructured. They typically offer the following features:
- Full text search
- Geospatial search
- Support for complex search expressions
- Stemming (reducing inflected words to their stem)
- Ranking and grouping of search results
- Distributed search for high scalability